In photolithography, a design is transferred onto a surface by shining a light through a mask (or reticle) of the design onto a photosensitive material covering the surface. The light exposes the photo-sensitive material in the pattern of the mask. A chemical process etches away either the exposed material or the unexposed material, depending on the particular process that is being used. Another chemical process etches into the surface wherever the photosensitive material was removed. The result is the design itself, either imprinted into the surface where the surface has been etched away, or protruding slightly from the surface as a result of the surrounding material having been etched away.
Photolithography is used for a variety of purposes, such as manufacturing micro-mechanical devices and integrated circuits (ICs). For ICs, a silicon wafer goes through several iterations of imprinting a design on the wafer, growing a new layer over the previously imprinted design, and imprinting another design on the new layer. The different designs on each layer interact electrically to form circuit components, such as transistors, transmission paths, and input/output pads.
Photolithography can make very small components. Huge numbers of small circuit components can fit within a given surface area. Current photolithography techniques routinely fit millions of circuit components onto a single chip. Market pressures, however, continually drive for smaller components, higher density, and greater functionality.
FIG. 1 illustrates one embodiment of a cross-sectional intensity profile 110 of light 120 projecting a feature 130 onto a surface 140 in a photolithographic process. The surface is covered with a photosensitive material. A certain intensity of light, dose 150, is needed to expose the photosensitive material. Below dose 150, the material is not adequately exposed to create an image. In which case, the edges 160 of the feature 130 resolve, or appear, at the transition between exposed and unexposed areas of the photosensitive material where the intensity profile 110 crosses the dose level 150.
The contrast of an edge is basically the slope of the intensity profile at the dose level. A steeper slope means that the edge is more sharply defined. A gradual slope means that the edge is less sharp or fuzzy. The sharper the contrast, the more precision and predictability there is in edge placement, and the smaller the features can be.
If a feature is large compared to the wavelength of the light, the intensity profile tends to be deep and sharp. As the feature size gets smaller however, the intensity profile gets shallower and broadens out. For instance, FIG. 2 illustrates two more intensity profiles, profile 210 and profile 230. Profile 210 corresponds to a feature 220 having a feature size that is large compared to a wavelength of the light. Profile 230 corresponds to a feature 240 having a feature size that is small compared to the wavelength.
This broadening of the intensity pattern as feature sizes near or drop below the wavelength of the light source creates a number of design challenges. The projected image no longer identically reflects the shapes of the features in the mask. Edge placement becomes increasingly less precise, often leading to the ends of lines being cut off and sharp corners being rounded. Neighboring features become increasingly interdependent as their intensity patterns overlap, often causing features to “bleed” into each other or not resolve at all.
An area of study called resolution enhancing technology (RET) is constantly in development to compensate for, or reduce, these effects in near- or sub-wavelength photolithographic processes. Examples of RETs include optical proximity correction (OPC), sub-resolution assist features (SRAFs), off-axis illumination, dipole illumination, and phase shift masks (PSM).
OPC moves feature edges in a mask, essentially shifting an intensity profile one way or another to move the projected edge. Other RETs also change the position of projected edges, but do so more by changing the shape of the intensity profile than by shifting the intensity profile.
For instance, SRAFs take advantage of the fact that intensity profiles of neighboring edges influence one another. SRAFs themselves are so narrow that their intensity profiles are not deep enough to resolve—hence the name “sub-resolution.” But, their intensity profiles can overlap with the intensity profiles of neighboring edges. In which case, SRAFs are features that are added to a mask near an existing feature, creating a combined intensity profile with a different contrast, changing the position of the projected edges.
Off-axis illumination and di-pole illumination are also RETS that change intensity profiles. Di-pole illumination is basically an extreme form of off-axis illumination. Edges that are oriented perpendicular to the orientation of the illumination have sharper intensity profiles and image more clearly than if illuminated by an on-axis light source.
PSM takes advantage of the interference characteristics of light.
RETs often use edge classifications to determine what kind of enhancement to apply to a particular edge. For instance, SRAFs are usually inserted in a design based on spacing. Spacing is the outward distance from an edge of a feature to another edge. Different spacing classifications, or ranges of spacings, often receive different SRAF treatment.
FIG. 3 illustrates spacing classifications for two features, feature 310 and feature 320. Spacing 315 is the distance between edges 330 and 340. In which case, edges 330 and 340 may be assigned to a spacing classification, or range of spacings, that includes spacing 315. Edge 350, however, has no opposing edge. In which case, edge 350 may be assigned to a spacing classification for isolated edges.
In the illustrated embodiment, the two different spacing classifications receive different SRAF treatment. Specifically, edges 330 and 340 receive SRAF 335 centered between them. Edge 350, on the other hand, receives a pair of SRAFs 355 at some predetermined distances 360 and 365.
For OPC, edges are often classified based on length and relation. For instance, FIG. 4 illustrates a feature 410 having several different edge classifications. Edge fragments at corner 420 may be classified as convex corner edge fragments, which are pushed out to form serif 425 to reduce the rounding of the corner in the projected image. Edge fragments at corner 430 may be classified as concave corner edge fragments, which are pushed in to form inverted serif 435, also to reduce rounding in the projected image. Edge fragments at line ends 440 and 450 may be classified as line end edge fragments, which are been pushed out to form hammer heads 445 and 455, respectively, to reduce line end cut-off in the projected image.
For di-pole illumination, or off-axis illumination, edges are often classified based on orientation. For example, di-pole illumination often uses two masks. One mask is illuminated with a horizontal di-pole and one mask is illuminated with a vertical di-pole. Since edges that are oriented perpendicular to the orientation of the di-pole have sharper intensity profiles and resolve more clearly, edges are usually classified as either horizontal or vertical and assigned to the appropriate mask. The corresponding space in the opposite mask includes a shield to prevent the area from being exposed by the other mask.
For PSM, edges are often classified so that neighboring features are assigned to different phases to reduce the influence the neighboring edges have on one another. Like di-pole illumination, PSM often involves two masks, a phase mask and a trim mask. In which case, like di-pole illumination, an edge assigned to one mask will often have a corresponding shield in the other mask.
At best, most classification systems used in resolution enhancing technologies (RETs) merely suggest that an edge may benefit from a particular enhancement. Spacing-based classifications usually only take into consideration a fixed number of neighboring edges. Edges that run diagonally through a design are often difficult to classify to either a horizontal or a vertical di-pole mask. And, features may have complex shapes that are interwoven with multiple neighbors, making it very difficult to classify edges of neighboring features to different phases in PSM.